In a network virtualization system, network controllers manage the network state to implement logical networks over a physical network. The network state is not a constant, and as the state changes, updates to the state must be distributed to the managed forwarding elements throughout the network. These updates to the network state may appear for at least three reasons. First, when logical policy changes because the network policy enforced by the logical pipeline is reconfigured (e.g., the updating of access control lists by an administrator of a logical network), the network state changes. Second, workload operational changes result in a change to the network state. For instance, when a virtual machine migrates from a first node to a second node, the logical view remains unchanged. However, the network state requires updating due to the migration, as the logical port to which the VM attaches is now at a different physical location. Third, physical reconfiguration events, such as device additions, removals, upgrades and reconfiguration, may result in changes to the network state.
These three different types of changes resulting in network state updates have different implications in terms of network state inconsistency (i.e., in terms of the network state not being up-to-date for a given policy or physical configuration). For instance, when the network state is not up to date because of a new policy, the logical pipeline remains operational and merely uses the old policy. In other words, while moving to enforce the new policies quickly is essential, it is typically not a matter of highest importance because the old policy is valid as such. Furthermore, the physical reconfiguration events come without time pressure, as these events can be prepared for (e.g., by moving VMs around within the physical network).
However, when the network state shared among the forwarding elements of the physical network has not yet captured all of the operational changes (e.g., VM migrations), the pipeline may not be functional. For example, packets sent to a particular logical destination may be sent to a physical location that no longer correlates to that logical destination. This results in extra packet drops that translate to a non-functional logical network, and thus the avoidance of such out-of-date network states should be given the utmost priority.
Accordingly, the network controller faces several challenges to maintain the network state. First, the virtualization itself requires precise control over the network state by the network controllers in order to enforce the correct policies and to implement the virtualization. Once the controllers become involved, the timescale for distributing updates becomes much longer than for solutions that exist purely within the data plane (e.g., traditional distributed Layer 2 learning). Second, the responsibility for the entire network state places a scalability burden on the controllers because the volume of the network state itself may become a source of complications for the controllers.